A specific QSAR model for proteasome inhibitors from Oleaeuropaea and Ficuscarica

Lahmadi, Ayoub; El-Aliani, Aissam; Kasmi, Yassine; Said, Elantri; Mohammed, El Mzibri; Aboudkhil, Souad

doi:10.6026/97320630014384

Cited by 2 publications

(1 citation statement)

References 33 publications

(37 reference statements)

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“…This higher activity could be due to the anthocyanins content of the H. sabdariffa ethanolic extract, which represented 0.23%. These are secondary metabolites with an already known proteasome inhibitory activity [31,32]. Consistently, the proteasome inhibition activity demonstrated by the HsEF was the result of the activity of anthocyanins, Hibester and Hib-carbaldehyde together.…”

Section: Evaluation Of Proteasome Inhibitionsupporting

confidence: 53%

Anti-Multiple Myeloma Potential of Secondary Metabolites from Hibiscus sabdariffa—Part 2

et al. 2021

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Multiple Myeloma (MM) is an aggressive tumor causing millions of deaths every year and currently available therapies are often unsuccessful or correlated with severe side effects. In our previous work we demonstrated that the Hibiscus sabdariffa hydroalcoholic extract inhibits the growth of the MM cell line and we isolated two metabolites responsible for the activity: Hib-ester and Hib-carbaldehyde. Herein we report their interaction with proteasome, one of the main targets in the fight against MM. The molecular modelling study outlined a good interaction of both compounds with the target and these results prompted us to investigate their potential to inhibit proteasome. Metabolites were then isolated from the calyces and an extract with a high content of Hib-ester and Hib-carbaldehyde was prepared. An anticancer profile was drawn, evaluating apoptosis, autophagy and proteasome inhibition, with the anticancer properties being mainly attributed to the Hib-ester and Hib-carbaldehyde, while the proteasome inhibition of the extract could also be ascribed to the presence of anthocyanins, a class of secondary metabolites already known for their proteasome inhibitory activity.

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Section: Evaluation Of Proteasome Inhibitionsupporting

confidence: 53%

Anti-Multiple Myeloma Potential of Secondary Metabolites from Hibiscus sabdariffa—Part 2

et al. 2021

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QSAR study of phenolic compounds and their anti-DPPH radical activity by discriminant analysis

Yuan

Xiao

et al. 2022

Sci Rep

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Phenolic compounds (PCs) could be applied to reduce reactive oxygen species (ROS) levels, and are used to prevent and treat diseases related to oxidative stress. QSAR study was applied to elucidate the relationship between the molecular descriptors and physicochemical properties of polyphenol analogues and their DPPH radical scavenging capability, to guide the design and discovery of highly-potent antioxidant substances more efficiently. PubMed database was used to collect 99 PCs with antioxidant activity, whereas, 105 negative PCs were found in ChEMBL database; their molecular descriptors were generated with Python's Rdkit package. While the molecular descriptors significantly related to the antioxidant activity of PCs were filtered by t-test. The prediction QSAR model was then established by discriminant analysis, and the obtained model was verified by the back-substitution and Leave-One-Out cross-validation methods along with heat map. It was revealed that the anti-DPPH radical activity of PCs was correlated with the drug-likeness and molecular fingerprints, physicochemical, topological, constitutional and electronic property. The established QSAR model could explicitly predict the antioxidant activity of polyphenols, thus were applicable to evaluate the potential of candidates as antioxidants.

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A specific QSAR model for proteasome inhibitors from Oleaeuropaea and Ficuscarica

Cited by 2 publications

References 33 publications

Anti-Multiple Myeloma Potential of Secondary Metabolites from Hibiscus sabdariffa—Part 2

Anti-Multiple Myeloma Potential of Secondary Metabolites from Hibiscus sabdariffa—Part 2

QSAR study of phenolic compounds and their anti-DPPH radical activity by discriminant analysis

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